Pathogenic Mutation of TDP-43 Impairs RNA Processing in a Cell Type-Specific Manner: Implications for the Pathogenesis of ALS/FTLD

Abstract Transactivating response element DNA-binding protein of 43 kDa (TDP-43), which is encoded by the TARDBP gene, is an RNA-binding protein with fundamental RNA processing activities, and its loss-of-function (LOF) has a central role in the pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). TARDBP mutations are postulated to inactivate TDP-43 functions, leading to impaired RNA processing. However, it has not been fully examined how mutant TDP-43 affects global RNA regulation, especially in human cell models. Here, we examined global RNA processing in forebrain cortical neurons derived from human induced pluripotent stem cells (iPSCs) with a pathogenic TARDBP mutation encoding the TDP-43K263E protein. In neurons expressing mutant TDP-43, we detected disrupted RNA regulation, including global changes in gene expression, missplicing, and aberrant polyadenylation, all of which were highly similar to those induced by TDP-43 knock-down. This mutation-induced TDP-43 LOF was not because of the cytoplasmic mislocalization of TDP-43. Intriguingly, in nonneuronal cells, including iPSCs and neural progenitor cells (NPCs), we did not observe impairments in RNA processing, thus indicating that the K263E mutation results in neuron-specific LOF of TDP-43. This study characterizes global RNA processing impairments induced by mutant TDP-43 and reveals the unprecedented cell type specificity of TDP-43 LOF in ALS/FTLD pathogenesis.


Introduction
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder caused by the degeneration of upper and lower motor neurons, leading to a progressive loss of motor function. Frontotemporal lobar degeneration (FTLD) is the second most common type of dementia after Alzheimer's disease and is characterized by progressive atrophy in the frontal and temporal lobes and by personality and behavioral changes. Transactivating response element DNA-binding protein of 43 kDa (TDP-43) was identified as a major component of pathologic inclusions found in the vast majority of patients with ALS and ;50% of patients with FTLD (Neumann et al., 2006). Moreover, previous studies reported mutations in the TARDBP gene encoding TDP-43 in patients with ALS and FTLD (Kabashi et al., 2008;Kovacs et al., 2009). These findings highlight a central role for TDP-43 in ALS/FTLD pathogenesis (S.C. Ling et al., 2013).
TDP-43 has various functions in RNA metabolism, including splicing, polyadenylation, transport, translation, and miRNA synthesis (S.C. Ling et al., 2013). Accumulating evidence suggests that TDP-43 loss-of-function (LOF) underlies the pathomechanism of ALS/FTLD. One particular target of TDP-43 LOF is RNA missplicing. TDP-43 LOF induces the cryptic splicing of a distinct group of genes, such as STMN2, which is also observed in patients with ALS/FTLD (Klim et al., 2019;Melamed et al., 2019;Prudencio et al., 2020). Notably, the pathogenesis of TDP-43 LOF is sometimes human-specific, requiring study in human cell models; for example, cryptic splicing of STMN2 was not conserved in mouse models (J.P. Ling et al., 2015). Therefore, human induced pluripotent stem cell (iPSC)-based disease models have great potential (Okano and Morimoto, 2022). However, TDP-43 knock-down has been mainly used for the characterization of RNA processing impairments in human iPSC-based disease models (Klim et al., 2019;Prudencio et al., 2020), and the link between pathogenic TARDBP mutations and RNA regulation has not been fully explored. Another unanswered question is the cell type specificity of the effect of TARDBP mutations. As TDP-43 is globally expressed in various organs, including the brain, liver, lung, and kidney (Sephton et al., 2010), it is mysterious why these mutations result in ALS and FTLD, which selectively affect the CNS. Thus, the potential cell type specificity of the effect of the mutant TDP-43 protein on RNA regulation should be investigated.
In this study, using human iPSC-based models, we examined the K263E variant of TDP-43, which was initially identified in a patient with FTLD (Kovacs et al., 2009), with a disrupted RNA binding capacity (H.J. Chen et al., 2019). Similar to TDP-43 knock-down, TDP-43 K263E affected various RNA processing machineries in iPSC-derived neurons. These impaired RNA processes included intron splicing and 39 polyadenylation regulation. In contrast to neurons, however, iPSCs and neural progenitor cells (NPCs) expressing TDP-43 K263E did not mimic TDP-43 LOF. This study characterizes global RNA processing impairments induced by mutant TDP-43 and indicates that mutant TDP-43 exhibits LOF in a cell type-specific manner.

Culture of undifferentiated iPSCs
Human iPSCs (201B7; Takahashi et al., 2007) were maintained in StemFit AK02 N medium (Ajinomoto). Cells were seeded at a density of 1.5 Â 10 4 cells/well in an iMatrix 511 (Laminin511E8; Wako)-treated six-well plate; 10 mM Y27632 (Nacalai) was only added for the first day. Culture media were changed every other day.

RNA sequencing
Total RNA was isolated from iPSCs and NPCs on day 12 and from neurons on day 36 with the RNeasy Mini kit (QIAGEN) with DNase I treatment. The quality of RNA (RNA integrity number; RIN) was assessed by Agilent 2100 Bioanalyzer (Agilent). The indexed cDNA libraries were prepared using the TruSeq stranded mRNA Library Preparation kit (Illumina) and sequenced using a NovaSeq6000 (Illumina) to obtain 150-bp paired-end reads at Macrogen. RNA-seq datasets of TDP-43 knockdown experiments from previous reports Klim et al., 2019;Melamed et al., 2019) were downloaded via the NCBI Sequence Read Archive (accession numbers SRR8083864-8, SRR8083871-75, SRR8083878-81, and SRR8144907-12). The RNA-seq dataset of ESCs with TDP-43 knock-down (Modic et al., 2019) was kindly provided by M. Modic (Francis Crick Institute). Raw fastq files were trimmed to remove low-quality bases and adapters using fastp (S. Chen et al., 2018) and were processed for further analyses.

Gene expression profiling
Salmon (Patro et al., 2017) was used to generate the TPM using the transcript index from the reference GRCh38 genome annotation (GENCODE release 33) to quantify gene expression levels. We identified differentially expressed genes (DEGs) using the DESeq2 suite of bioinformatics tools (Love et al., 2014) with a cutoff of 0.05 for Benjamini-Hochberg adjusted p values and a cutoff of 0.25 for the log2 fold change ratio. Principal component analysis (PCA) was performed using vst transformation of estimated counts based on intersections between DEG lists of two independent TDP-43 knock-down experiments from the studies by Klim et al. (2019) and Melamed et al. (2019). Our RNAseq data were projected onto this PCA.
Read alignment to the genome and alternative splicing analyses HISAT2 (D. Kim et al., 2019) was used to map sequencing reads to the human GRCh38 genome. Coverage tracks were visualized with Integrative Genomics Viewer (IGV). Counts at individual exons were calculated from the HISAT2aligned data using featureCounts (Liao et al., 2014) with the gene annotation from Ensembl (release 104), and the differential exon usage analysis was performed using DEXseq (Anders et al., 2012) with a cutoff of 0.01 for Benjamini-Hochberg adjusted p values. Differentially spliced intron clusters were analyzed from the HISAT2-aligned data without existing isoform annotations by LeafCutter (Li et al., 2018). Briefly, splice junction reads were extracted with RegTools (Cotto et al., 2021) using a minimum of 6 bp as an anchor on each side of the junction. Junctions from each sample were then clustered using leafcutter_-cluster_regtools_py3.py (minclureads = 10). Differential intron splicing was calculated using leafcutter_ds.R. In addition to LeafCutter analysis, we also evaluated splice variants of UNC13A and STMN2 by filtering reads that span the junctions between normal exons and cryptic exons as previously described (Ma et al., 2022). Junction spanning reads were filtered and quantified using junc-tion_spanning_reads.sh.

Alternative polyadenylation analysis
QAPA (Ha et al., 2018) was used to quantify TPM for individual alternative polyadenylation sites (PASs) from RNA-seq data. The 39 untranslated region (UTR) sequence was extracted from GRCh38 genome by qapa fasta based on the precomplied annotation available on the QAPA GitHub page (https://github.com/morrislab/ qapa). Salmon index was prepared using this 39 UTR sequence. 39 UTR isoform usage was then quantified using "salmon quant" and "qapa quant." PASs with TPMs .5 were retained for further analysis. For each gene, genelevel relative PAS usage was summarized using a metric W (Goering et al., 2021). Each PAS within a gene was assigned a value, m, which is defined as its position within this proximal-to-distal ordering, beginning with 1, to calculate W. Each gene was also assigned a value, n, which is defined as the number of distinct PASs that it contains. The expression level of each PAS (TPM m ) was evaluated, and gene-level PAS usage was summarized using the following formula: Analysis of 39 end-seq data The 39 end-seq datasets from a previous report (Modic et al., 2019) were downloaded from the European Nucleotide Archive (accession numbers ERR1642497 and ERR1642501). Fastp was used for quality and adapter trimming, and sequencing reads were aligned to the human GRCh38 genome using HISAT2. Coverage tracks were visualized using IGV.
Quantitative RT-PCR cDNA was prepared by using a ReverTraAce qPCR RT kit (Toyobo). The qPCR analysis was performed with TB Green Premix Ex Taq (TAKARA) using a ViiA 7 real-time PCR system (Applied Biosystems) according to the manufacturer's instructions. Values were normalized to ACTB levels. Data were analyzed using the comparative (DDCt) method. The primers used for qPCR were as follows:

Immunocytochemistry
Neurons cultured until day 36 were fixed with 4% paraformaldehyde for 15 min at room temperature and then washed three times with PBS. After an incubation with blocking buffer (PBS containing 5% normal goat serum and 0.3% Triton X-100) for 30 min at room temperature, the cells were incubated overnight at 4°C with primary antibodies at the following dilutions: TDP-43 (rabbit, Proteintech, 10782-2-AP, 1:200) and TUBB3 (mouse, Sigma, T8660, 1:500). The cells were again washed three times with PBS and incubated with secondary antibodies conjugated to Alexa Fluor 488 or 555 (Life Technologies) and Hoechst 33342 (Dojindo Laboratories) for 1 h at room temperature. After three washes with PBS and one wash with distilled water, the samples were mounted on slides and examined using an LSM-710 confocal laser scanning microscope (Carl Zeiss). Line-scan analysis was performed using ImageJ software. The resulting values were normalized to the maximum intensity. For the analysis of TDP-43 localization, TUBB3 staining was used to determine the cell body as the region of interest, and then Pearson's correlation coefficient was calculated for TDP-43 and Hoechst staining using the Coloc2 plugin.

Data availability
All the sequencing data have been deposited in the NCBI's Gene Expression Omnibus and are accessible through GEO Series accession number GSE195689 (201B7 iPSC) and GSE196144 (otherwise).

Results
Gene expression profile of cortical neurons derived from isogenic iPSCs harboring the TDP-43 K263E mutation In the present study, we focused on the function of the mutant TDP-43 K263E protein (Fig. 1A). This mutation of the TARDBP gene was identified in a patient with FTLD (Kovacs et al., 2009) and is suggested to reduce the RNA binding capacity of TDP-43 (H.J. Chen et al., 2019). We introduced a homozygous K263E mutation in healthy wild-type human iPSCs using the CRISPR/Cas9 system ( Fig. 1B,C). Forebrain cortical neurons were generated from control (wild-type) and TDP-43 K263E iPSCs by dual SMAD and Wnt inhibition, respectively ( Fig. 1D; Imaizumi et al., 2015;Sato et al., 2021). This mutant genotype did not affect the gene expression of markers for pluripotency, neural progenitors, and neurons ( Fig. 1E). In addition, we found no difference in neuronal induction efficiency (Fig. 1F). These data indicate that the pluripotency maintenance and the neuronal induction were equivalent between wild-type and TDP-43 K263E iPSCs.
We performed an RNA-seq analysis of these iPSC-derived cortical neurons. Data quality was assured by RIN, Phred quality score, and a uniform mapping rate for all samples (Extended Data Fig. 1-1A-E). The global gene expression profile was measured, and the analysis of DEGs identified 550 genes that were significantly differentially expressed between wild-type and TDP-43 K263E iPSC-derived neurons ( Fig. 1G; Extended Data Fig. 1-1F). Fold changes of these DEGs were relatively small, but this is consistent with other reports (Klim et al., 2019;Melamed et al., 2019). Among these DEGs, the most significantly altered gene was STMN2. As previous studies have reported that STMN2 is the gene most affected by TDP-43 knock-down (Klim et al., 2019;Melamed et al., 2019), we reanalyzed RNA-seq datasets from these previous studies and compared the effect of TDP-43 K263E and TDP-43 knock-down on gene expression. TDP-43 knockdown downregulated STMN2 expression quite similarly to TDP-43 K263E (Fig. 1H). PCA grouped TDP-43 K263E and TDP-43 knock-down cells into the same cluster along PC2, whereas the data from the study by Melamed and colleagues were grouped separately on PC1 (Fig. 1I). When comparing gene expression between TDP-43 K263E and TDP-43 knock-down neurons, a strong correlation was observed between TDP-43 K263E and TDP-43 knockdown neurons, except for the expression of TARDBP (Fig.  1J,K). Collectively, TDP-43 K263E and TDP-43 knock-down exerted similar effects on gene expression, indicating that K263E corresponds to an LOF mutation.
Characterization of missplicing indicates the similarity between TDP-43 K263E and TDP-43 knock-down TDP-43 plays a pivotal role in RNA processing, and previous reports suggest that STMN2 loss on TDP-43 knockdown is because of cryptic exon inclusion (Klim et al., 2019;Melamed et al., 2019). Notably, we identified the same cryptic splice events in TDP-43 K263E neurons ( Fig.  2A). This observation suggests that TDP-43 K263E induced RNA missplicing; therefore, we analyzed differential exon usage between wild-type and TDP-43 K263E neurons using RNA-seq datasets. We identified 299 genes whose exon usages were significantly altered (Fig. 2B). We repeated the same exon usage analyses for TDP-43 knock-down datasets, and fold changes in exon usage induced by TDP-43 K263E were highly similar to those induced by TDP-43 knock-down (Fig. 2C). Notably, both in TDP-43 K263E and in TDP-43 knock-down cells, we detected the exclusion of POLDIP3 exon 3 (Fig. 2D), which has previously been associated with TDP-43 deficits (Shiga et al., 2012). Based on these data, RNA missplicing induced by TDP-43 K263E results from TDP-43 LOF.
The exon usage analysis is based on existing isoform annotations, but disease-relevant missplicing often occurs in      unannotated introns. We performed an annotation-free differential splicing analysis to characterize global changes in intron splicing (Li et al., 2018). We detected cryptic splicing not only in STMN2 but also in various gene targets, including PFKP, DNAJC5, KALRN, SYT7, and UNC13B, all of which have been shown to be misspliced in TDP-43 knock-down models (Fig. 2E   reads in only a subset of samples of TDP-43 K263E neurons, whereas there were no spanning reads in wild-type neurons (Extended Data Fig. 2-1A-C). A similar analysis focusing on STMN2 cryptic exon robustly detected splicing change by mutant TDP-43 (Extended Data Fig. 2-1D-F). These results raised two possibilities: one is that TDP-43 K263E has little if any effect on UNC13A splicing; and the other is that RNA sequencing could not well capture UNC13A cryptic exons despite the fact that missplicing occurs. We found that both wild-type and isogenic TDP-43 K263E cells harbored homozygous risk SNP/indels (rs12973192, rs12608932, and rs56041637) that increase the efficiency of UNC13A cryptic splicing on TDP-43 loss (Extended Data Fig. 2-1G; Brown et al., 2022;Ma et al., 2022). Thus, the cryptic splicing of UNC13A in these cells is expected to be drastically enhanced by TDP-43 LOF, which supports the second possibility. Indeed, RT-qPCR analysis revealed that UNC13A cryptic splicing was reproducibly increased in TDP-43 K263E neurons (Extended Data Fig. 2-1H). These data suggest that UNC13A missplicing was actually occurring, but RNA-seq analysis was not sensitive enough to detect it. The low sensitivity of RNA-seq analysis to detect UNC13A missplicing was also supported by the finding that analyses using the data from Klim et al. (2019) and Melamed et al. (2019) similarly detected UNC13A missplicing in only a subset of samples (Extended Data Fig. 2-1I).

TDP-43 autoregulation through RNA 39 end processing is impaired by TDP-43 K263E
While gene expression profiling and splicing analyses indicated the similarity between TDP-43 K263E and TDP-43 knock-down, TARDBP expression was upregulated in TDP-43 K263E neurons (Fig. 1D). TARDBP expression was autoregulated by TDP-43 itself; namely, the binding of TDP-43 to its own mRNA changes the processing of the 39 UTR, finally leading to a decrease in the mRNA level ( Fig. 3A; Ayala et al., 2011;Eréndira Avendaño-Vázquez et al., 2012;Weskamp and Barmada, 2018). Indeed, we observed decreased splicing events in the 39 UTR of the TARDBP mRNA in TDP-43 K263E neurons (Fig. 3B), suggesting that K263E mutations affect the autoregulatory properties of TDP-43. We focused on alternative polyadenylation, which results in the formation of multiple transcript isoforms with distinct 39 UTRs, to further investigate 39 UTR regulation. We quantified the usage level of each PAS from RNA-seq data (Ha et al., 2018), and gene-level PAS usage was summarized as the metric W (Goering et al., 2021). Genes with exclusive usage of the most proximal PAS were assigned W values of 0, whereas genes with exclusive usage of the most distal PAS were assigned W values of 1 (Fig. 3C). The use of multiple PASs will result in W values between 0 and 1, depending on the relative usage of individual sites. With this metric W, we found that the 39 UTR was shortened in TDP-43 K263E neurons compared with wild-type neurons (Fig. 3D). These results imply that the K263E mutation impairs the 39 UTR regulation of the TARDBP mRNA, leading to the collapse of autoregulation.
Global disruption of 39 end processing TDP-43 regulates not only its own mRNA but also a broad range of 39 end processing events (Rot et al., 2017). Thus, we performed the differential PAS usage analysis with the metric W and identified 70 genes whose PAS usage was significantly altered between wild-type and TDP-43 K263E neurons (Fig. 3E). The proximal PAS of PPP2R2D was preferentially used in wild-type neurons; on the other hand, TDP-43 K263E neurons used the lengthened 39 UTR (Fig. 3F). The 39 UTR of SMC1A was shifted similarly, but in the opposite direction (Fig. 3F). These shifts are consistent with a recent study that identified genes with PAS switches induced by TDP-43 depletion (Hallegger et al., 2021). Collectively, these results suggest that TDP-43 K263E affects RNA 39 end processing of various genes because of the impaired TDP-43 function.
Cell type specificity of disrupted RNA processing induced by TDP-43 K263E We performed RNA-seq of iPSCs and NPCs expressing wild-type or K263E variant TDP-43 to test whether these RNA processing disruptions induced by TDP-43 K263E were also present in cell types other than neurons (Extended Data Fig. 1-1A-E). TARDBP was expressed at similarly high levels among iPSCs, NPCs, and neurons (Fig. 5A). In contrast to neurons, we did not find a drastic change of TARDBP expression in TDP-43 K263E iPSCs and NPCs compared with wild-type cells (Fig.  5B). We reanalyzed the RNA-seq data from ESCs with TDP-43 knock-down (Modic et al., 2019), and the comparison of the gene expression profiles showed no correlation between TDP-43 K263E iPSCs and TDP-43 knock-down ESCs (Fig. 5C), suggesting that the K263E mutation does not phenocopy TDP-43 knock-down in iPSC cultures. This dissimilarity between TDP-43 K263E iPSCs and TDP-43 knock-down ESCs was also evident in the differential exon usage analysis, in which exon usage fold changes induced by TDP-43 K263E were quite distinct from those induced by TDP-43 knock-down (Fig.  5D). Remarkably, the exclusion of POLDIP3 exon 3 was only observed in TDP-43 knock-down ESCs but not in TDP-43 K263E iPSCs (Fig. 5E). Moreover, the K263E mutation drastically decreased intron 7 splicing in the 39 UTR of TARDBP only in neurons; in contrast, this splicing event was rarely affected in TDP-43 K263E iPSCs and NPCs (Fig. 5F). In the analysis of the 39 end processing of the PPP2R2D mRNA, RNA-seq and 39 end-seq revealed that the 39 UTR was lengthened in TDP-43 knockdown ESCs, but TDP-43 K263E iPSCs did not exhibit this PAS switch (Fig. 5G). Taken together, the data from nonneuronal cells, especially iPSCs, indicate that TDP-43 K263E did not mimic the RNA processing impairment induced by TDP-43 depletion. This result is the opposite of the close relationship between the K263E mutation and LOF in neurons (Fig. 5H).

Discussion
Human iPSC-based disease models have remarkable potential to clarify disease pathogenesis and to discover effective therapies because of the discrepancy between patients and animal models (Okano and Yamanaka, 2014;Imaizumi and Okano, 2021). Previous studies of human iPSC-based models revealed RNA misprocessing induced by TDP-43 LOF; however, these studies largely used a knock-down strategy for recapitulating TDP-43 LOF (Klim et al., 2019;Prudencio et al., 2020), and the effect of pathogenic mutations of TDP-43 on global RNA regulation has not been extensively investigated. In the present study, we characterized global RNA processing impairments induced by the K263E mutation in iPSC-derived neurons. Consistent with the disrupted RNA binding capacity of TDP-43 K263E (H.J. Chen et al., 2019), substantial similarity exists between our mutant model and the knock-down system, indicating that pathogenic TDP-43 mutation induces TDP-43 LOF in neurons. Notably, our mutant model exhibited a defect in TDP-43 autoregulation, which cannot be investigated in a knock-down system.
Previous reports have suggested several distinct but overlapping effects of mutations on TDP-43 functions, including cytoplasmic mislocalization, an increased tendency to aggregate, and a decreased RNA binding capacity (Prasad et al., 2019). Cellular models overexpressing the TDP-43 K263E mutant indicate that K263E disrupts the RNA binding capacity of TDP-43 and enhances intranuclear TDP-43 aggregation or liquid shell formation (H.J. Chen et al., 2019;Yu et al., 2021). Although our results are consistent with the reduced RNA binding capacity of TDP-43 K263E , we did not observe aggregation or droplets of TDP-43 in our iPSC-derived neurons. This inconsistency is probably because of the difference in TDP-43 expression levels. Excess TDP-43 expression might enhance TDP-43 aggregation, but endogenous TDP-43 expression does not. This finding is supported by a neuropathological study of a patient with FTLD carrying the K263E mutation, in which intranuclear TDP-43 inclusions were not observed in the cerebral cortex (Kovacs et al., 2009).
Additionally, cytoplasmic TDP-43 inclusions were indeed observed in this K263E carrier patient (Kovacs et al., 2009). In contrast to this pathologic observation, continued (normalized to ACTB; n = 3). G, Top panel, RNA-seq read coverage mapped to the genomic region of PPP2R2D in wild-type and TDP-43 K263E  iPSC-derived neurons did not exhibit cytoplasmic mislocalization of TDP-43, consistent with previous reports using iPSC-derived neurons expressing other pathogenic TDP-43 mutations (Klim et al., 2019). On the other hand, cytoplasmic TDP-43 accumulation was observed in neurons directly converted from fibroblasts expressing another pathogenic TDP-43 mutation, N352S (Melamed et al., 2019). A recent study of Huntington's disease suggested that age-related signatures were different between iPSC-derived neurons and directly converted neurons; therefore, pathogenic huntingtin aggregates were detected only in converted neurons but not in iPSC-derived neurons (Victor et al., 2018). This study revealed that the induction of pluripotency erased age marks, while direct neuronal conversion maintained age-related signatures. Therefore, direct neuronal conversion would be beneficial for investigating age-associated phenotypes associated with TDP-43 mutations reflecting more advanced pathology.
Our results strongly suggest the cell type-specific function of TDP-43 K263E . TDP-43 LOF was only observed in neuronal cultures, whereas iPSCs and NPCs did not suffer from K263E mutation. The effect of TDP-43 mutation is often tested in nonneuronal cell lines, and comparisons among cell lines have been seldom studied. Thus, the findings for the TDP-43 mutant may need to be revisited in terms of the cell types tested. This cell type specificity is also important for the pathogenesis of ALS/FTLD. CNSspecific lesions in patients with ALS/FTLD do not match the observation that TDP-43 is expressed in various organs in the body (Sephton et al., 2010). Neuron-specific TDP-43 LOF may account for CNS-specific pathology. Although we do not yet know the mechanism of cell typespecific LOF, a neuron-specific cofactor of TDP-43 might have a role. Regardless, this study provides insights into the unprecedented cell type specificity of TDP-43 LOF and provides new opportunities for advancing ALS/FTLD research.